MOMA artists

Data source

The artists dataset contains 15,087 records, representing all the artists who have work in MoMA’s collection and have been cataloged MOMA’s database. The source of the data is https://github.com/MuseumofModernArt/collection.

Analysis and Results

library(plyr)
library(ggplot2)
Data = read.csv("MOMA_clean.csv")  

1. Explore artworks created by male or female artist were being displayed more often in MOMA and whether the display time span have correlation with gender.

a.

ggplot(Data, aes(x = Gender)) + geom_bar() 

As was shown in the bar graph, male artists whose artwork were displayed in MOMA were about 8 times higher than female artists. The result was very different from my assumption, since that I used to believe women were more gifted in art area comparing to men. But then I understood that talented or not may not be the only index to measure whether an artist could have their artworks displayed in museum or not. Social norm, financial support and art education may be other factors that impact whether the artists could have their work displayed in the museum.

b.

ggplot(Data, aes(y = TimeSpan, x = Gender, colour = TimeSpan, group =1)) + geom_jitter() + stat_summary(fun.y=mean, colour="red", geom="line", size = 2)

To dig deeper into the gender differences of artists that have their work displayed in MOMA, and how long were their artworks were displayed in the museum, I added TimeSpan as another variable to refer to. As you can see, the jitter graph plotted out each data point, making it easier to perceive the trend between gender and TimeSpan. From the graph, we could infer that the median of women display time span were slightly higher than men, but not of immense significance. In short, I would say that there are no obvious differences between the display time of the artwork from artists of different genders.

2. When it comes to display artworks from artists of different nationalities, does MOMA has any preference? or from another aspect, does artists of different nationalities have preferences in whether to apply for display in MOMA. (About amount of artists with different nationalities)

Data$Nationality <- with(Data, reorder(Nationality, Nationality, function(x) -length(x)))
ggplot(Data, aes(x = Nationality, colour = Gender)) + geom_bar() + theme(axis.text.x = element_text(angle = 45, hjust = 1))

It is straightforward to me that located in New York, American artists is the top 1 group in the nationality list that MOMA displayed. As was showned, the top 5 stands out in the graph, being American, French, German, British and Italian. It is interesting that from the top displayed nationality to the less displayed, the bar graph is approximately logarithmically decayed.

Next, let’s look at whether gender and nationality has any relationship with each other. Being encoded in color, it is easy to see that merely all (except artists from Paraguayan) the artists with non-dominant (in the right hand side of the y-axis) nationality, were male artists. I supposed the reasons behind this in some countries, female artists might be suppressed in the art area, which is to say, they don’t have the education, financial support or environment to cultivate their talents in the art area.

3. Artists of which nationalities have their artworks displayed in MOMA for a comparatively longer time? (About display time span)

p <- ggplot(Data, aes(x= reorder(Nationality, TimeSpan, FUN=median), y=TimeSpan, fill = Nationality)) + theme(axis.text.x = element_text(angle = 45, hjust = 1))
p + geom_boxplot()

The median of all the nationalities were located approximately between 40 - 100 year in the graph. There are 4 outliers when it comes to the q1 of each y column (displayed in MOMA for over 120 years), being Russian, Swiss, German and Argentine.

p <- ggplot(Data, aes(x= reorder(Nationality, TimeSpan, FUN=median), y=TimeSpan, fill=Gender)) + theme(axis.text.x = element_text(angle = 60, hjust = 1))
p + geom_boxplot()

Though it was mentioned in analysis 2 that artists from non-dominanat display nationalities were mostly male, it is astonished to me to find out that for countries that have both male and female artists displayed their artworks, women have longer display TimeSpan than men. To be more specific, 15 countries were that women have higher median TimeSpan out of 22 countries with both female and male artists displayed their artworks in MOMA.

4. Are there any noticeable relationships between display period of the artworks by artists and nationality of the artsits in MOMA?

p <- ggplot(Data, aes(x = Nationality, y = TimeSpan, colour = Nationality, group=1))+theme(axis.text.x = element_text(angle = 45, hjust = 1))
p + geom_jitter() + stat_summary(fun.y=mean, colour="red", geom="line", size = 2)

From the line that connects the median of display time periods, I could conclude that artworks from almost artists of all nationalities have about a 75 year display time in MOMA. There are no significant positive or negative relationship between display time period and the artists nationality. However, there are several outliers in the graph that deviates from the 75 year line, which I think is due to the fact that in those columns, their were very few data point; therefore, not representative.